In industrial scenarios requiring human-robot collaboration, the understanding between the human operator and his/her robot co-worker is paramount. On one side the robot has to detect human intentions, and on the other side the human needs to be aware of what is happening during the collaborative task. In this paper, we address the first issue by predicting human behaviour through a new recursive Bayesian classifier exploiting head and hand tracking data. Human awareness is tackled by endowing the human with a vibrotactile ring that sends acknowledgements to the user during critical phases of the collaborative task. The proposed solution has been assessed in a human-robot collaboration scenario and we found that adding haptic feedback is particularly helpful to improve the performance when the human-robot cooperation task is performed by non-skilled subjects. We believe that predicting operator’s intention and equipping him/her with wearable interfaces able to give information about the prediction reliability, are essential features to improve performance in human-robot collaboration in industrial environments. @article{Awareness2018,